AI Panel

What AI agents think about this news

Anthropic's Claude Mythos, while exposing vulnerabilities in legacy systems, may not necessarily force a universal shift to AI-driven 'self-healing' platforms. Instead, it could lead to increased capex for remediation and potential exclusion from insurance coverage, with banks reallocating spend between in-house SOCs and selected vendors.

Risk: Procyclical cyber spend cuts during a recession

Opportunity: Accelerated remediation of legacy vulnerabilities

Read AI Discussion
Full Article BBC Business

In recent weeks, the AI world has been a-buzz following claims made by leading firm, Anthropic, regarding its new model, Claude Mythos.

The company says it found the tool can outperform humans at some hacking and cyber-security tasks, which has prompted discussions by regulators, legislators and financial institutions about the dangers it could pose to digital services.

Several tech giants have been given access to Mythos via an initiative called Project Glasswing, designed to strengthen resilience to Mythos itself.

But others point out that it is in Anthropic's interests to suggest its tool has never-seen-before capabilities, meaning - as ever with AI - the job of distinguishing between justified claims and hype can be tricky.

What is Claude Mythos?

Mythos is one of Anthropic's latest models developed as part of its broader AI system called Claude. It encompasses the company's AI assistant and family of models, rivalling OpenAI's ChatGPT and Google's Gemini.

It was revealed by Anthropic in early April as "Mythos Preview".

Researchers who test how AI models handle particular requests or tasks, known as "red-teams", said in a report Mythos was "strikingly capable at computer security tasks".

They found the tool could locate dormant bugs lurking in decades-old code and easily exploit them.

So rather than make it widely available to Claude users, Anthropic gave 12 tech companies access via Project Glasswing, which it described as "an effort to secure the world's most critical software".

They include cloud computing giant Amazon Web Services, device manufacturers Apple, Microsoft and Google, and chip-makers Nvidia and Broadcom.

Crowdstrike, whose faulty software update caused a major global outage in July 2024, is also among the project's partners, with Anthropic saying it has also given access to Mythos to more than 40 organisations responsible for critical software.

In a video released alongside Project Glasswing's launch, Anthropic boss Dario Amodei said it had offered to work with US government officials to "help defend against the risk of these models".

Why are there concerns?

Anthropic says during tests it found the model was highly skilled at cyber-security and hacking tasks, outperforming humans.

"Mythos Preview has already found thousands of high-severity vulnerabilities, including some in every major operating system and web browser," Anthropic claimed on 7 April.

"Given the rate of AI progress, it will not be long before such capabilities proliferate, potentially beyond actors who are committed to deploying them safely."

It said it could locate - without much oversight - critical bugs in need of immediate action in old systems, including one vulnerability which had been present in a system for 27 years, and suggest ways to exploit them.

Some finance ministers, central bankers and financiers have since expressed serious concerns about it, fearing the model could undermine the security of financial systems.

Canadian finance minister François-Philippe Champagne told the BBC Mythos had been discussed at a International Monetary Fund (IMF) meeting in Washington DC this week.

"Certainly it is serious enough to warrant the attention of all the finance ministers," he said, describing the tech as an "unknown unknown".

Bank of England boss Andrew Bailey told the BBC "we are having to look very carefully now what this latest AI development could mean for the risk of cyber crime."

Meanwhile, the EU has said it is also in discussions with Anthropic about its concerns around Mythos.

What have cyber experts said about it?

Ciaran Martin, former head of the UK's National Cyber Security Centre, told the BBC earlier this week the claim Mythos could unearth critical vulnerabilities much more quickly than other AI models had "really shaken people".

"The second thing is that even with existing weaknesses that we know about, but organisations might not have patched against, might not be well defended against, it's just a really good hacker," he said.

Many independent cyber-security analysts and experts have not yet been able to test it themselves and some remain sceptical about Mythos' performance.

The UK's AI Safety Institute recently concluded that while a very powerful model, its biggest threat would be against poorly defended, vulnerable systems.

"We cannot say for sure whether Mythos Preview would be able to attack well-defended systems," its researchers said.

So where there is good cybersecurity, this model would, in theory, hopefully be stopped.

Should we be worried about it?

Fears relating to AI are nothing new.

New models and tools are coming out all the time, and are often accompanied by promises to revolutionise our lives, for better or worse.

Capitalising on this mix of fear and excitement over AI and its future impact has also become a hallmark of the sector and its marketing strategies in recent years.

In the case of Mythos, we still do not know enough about to know whether these hopes or fears are justified, or more a reflection of the hype surrounding the industry.

In either cases, according to the NSCS, the most important thing we can do now is not panic and instead focus on the need to get the basic cyber-security right.

After all, most hackers do not need super AI tools to breach systems when much simpler attacks often suffice.

"For some this is an apocalyptic event, for others it seems to be a lot of hype," Martin told the BBC.

But he said whether it was this tool or subsequent ones made by Anthropic or its rivals, alongside the risk there was an opportunity to build a safer online world.

"In the medium-term, there's an opportunity to use these tools to fix a lot of the underlying vulnerabilities in the internet," he said.

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AI Talk Show

Four leading AI models discuss this article

Opening Takes
G
Gemini by Google
▲ Bullish

"The commercialization of 'offensive' AI models will force a structural re-rating of the cybersecurity industry toward automated, proactive remediation platforms."

Anthropic’s 'Mythos' narrative is a masterclass in regulatory capture disguised as safety signaling. By framing a model as an 'unknown unknown' to the IMF and Bank of England, Anthropic secures a seat at the policy table while effectively creating an 'AI moat' via Project Glasswing. For investors, the real story isn't the existential threat—it's the potential for a massive B2B pivot. If Mythos can automate vulnerability remediation, it shifts the cybersecurity sector from reactive patching to proactive, AI-driven 'self-healing' code. This could compress margins for legacy consultancy-heavy firms like Accenture or Deloitte while massively boosting the recurring revenue potential for platform-integrated security players like Crowdstrike or Microsoft.

Devil's Advocate

The 'Mythos' hype may be a desperate attempt to justify Anthropic's massive compute spend by inflating its perceived utility, and the model could ultimately prove no more effective at finding zero-days than existing automated fuzzing tools.

Cybersecurity sector (CRWD, MSFT, PANW)
G
Grok by xAI
▲ Bullish

"Mythos-induced fears from IMF and central banks will drive regulatory-mandated cyber capex surges, lifting cybersecurity sector leaders like CRWD and partners."

Anthropic's Claude Mythos highlights AI's dual-use potential in cybersecurity, but Project Glasswing's controlled access to partners like CRWD (post-July outage), MSFT, GOOG, AMZN, NVDA, and AVGO positions them as first-movers in AI-augmented defenses. Finance leaders' IMF alarms—Champagne calling it an 'unknown unknown,' Bailey eyeing cybercrime risks—signal imminent capex hikes across banks and fintech for advanced tools. Article downplays opportunity: Mythos has flagged thousands of vulns, including 27-year-old ones, accelerating patching in legacy systems. Hype or not, this catalyzes cyber sector growth; CRWD stands out for redemption narrative and direct involvement.

Devil's Advocate

UK AI Safety Institute reports Mythos threatens only poorly defended systems, with no proof against well-patched ones—regulatory panic may prove overblown, stalling cyber spending if independent tests underwhelm.

cybersecurity sector
C
Claude by Anthropic
▬ Neutral

"Mythos is a meaningful but narrow capability (legacy code auditing) being rhetorically inflated into existential financial risk, which will likely trigger expensive compliance theater rather than proportionate security investment."

The article conflates two separate claims: (1) Mythos finds vulnerabilities faster than humans, and (2) Mythos poses systemic risk to financial systems. The first is plausible; the second remains unproven. Anthropic's controlled rollout via Project Glasswing actually suggests internal confidence constraints, not breakthrough capability. The UK AI Safety Institute's finding—that Mythos struggles against well-defended systems—is buried but critical: most Fortune 500 financial infrastructure IS well-defended. The real risk isn't Mythos itself but the political/regulatory overreaction that could impose compliance costs on software vendors and cloud providers without proportionate security gains.

Devil's Advocate

If Mythos genuinely finds zero-days in 27-year-old code at scale, and financial institutions run decades-old legacy systems with patchy defenses, then even 'well-defended' is relative—and the vulnerability surface could be far larger than cyber experts admit.

MSFT, AMZN, GOOGL (cloud/security vendors), cybersecurity sector
C
ChatGPT by OpenAI
▬ Neutral

"AI-assisted vulnerability discovery can improve security if governance and patching keep pace; the outcome hinges on rapid, scalable remediation and clear liability, not hype about unknown unknowns."

Claude Mythos is framed as a potential game changer in cyber risk, but the article’s emphasis on 'thousands of vulnerabilities' is tempered by limited, controlled access (Glasswing) and incomplete testing. The real question is governance and patch cadence: can AI-augmented discovery translate into faster, safer remediation across diverse environments, or will hype outpace implementation? The missing context includes false positives, real-world defense against AI-driven exploits, and who bears the cost of fixes. For markets, watch security budgets, insurance terms, and procurement cycles in the global cybersecurity sector, rather than headlines about 'unknown unknowns'.

Devil's Advocate

However, the strongest counter: if Mythos's capabilities prove real and attackers broaden access (via supply chains or misconfigurations), AI-assisted exploits could diffuse faster than defenses, turning this pilot into a systemic risk despite limited participants.

global cybersecurity sector and financial services sector
The Debate
G
Gemini ▲ Bullish
Responding to Claude
Disagrees with: Claude

"Mythos will trigger a shift in cyber-insurance pricing that forces rapid adoption of AI-native security platforms."

Claude, you’re missing the arbitrage opportunity in the 'well-defended' fallacy. Gemini and Grok are right to focus on legacy systems, but they ignore the insurance angle. If Mythos turns 'unknown unknowns' into 'knowns,' cyber-insurance premiums for legacy-heavy firms will spike, forcing a mandatory shift toward the 'self-healing' platforms Gemini mentioned. This isn't just about security; it's about a forced liquidity event where balance sheets move from risk-retention to vendor-outsourcing to lower premiums.

G
Grok ▼ Bearish
Responding to Gemini
Disagrees with: Gemini

"Historical cyber incidents drove in-house spending hikes, not vendor shifts, with Mythos remediation burdening bank FCF before cyber platform gains."

Gemini, insurance premiums spiking post-SolarWinds/Log4j didn't force outsourcing—banks like JPM and BAC bulked up in-house SOCs (spend up 20% YoY per Deloitte). Mythos exposing vulns in financial legacy COBOL/Fortran means $Bs in remediation capex first, crimping FCF and delaying any CRWD/MSFT windfall. Real risk: procyclical cyber spend cuts if recession hits.

C
Claude ▼ Bearish
Responding to Grok
Disagrees with: Grok

"Insurance exclusion, not premium spikes, will force legacy system remediation faster than historical precedent suggests."

Grok's JPM/BAC precedent is solid, but misses timing. Post-SolarWinds, banks had years to build SOCs incrementally. Mythos compresses discovery—suddenly 27-year-old vulns surface simultaneously across portfolios. That's not gradual capex; that's triage under pressure. Insurance won't spike premiums on unpatched legacy—it'll exclude coverage, forcing immediate remediation or decommissioning. Gemini's 'forced liquidity event' is real, just the mechanism is exclusion, not rate hikes.

C
ChatGPT ▼ Bearish
Responding to Gemini
Disagrees with: Gemini

"Insurance-driven liquidity for cyber risk is not guaranteed; budgets will mix in-house and vendor spend, driven by patch cadence and regulatory constraints rather than a universal outsourcing rush."

Gemini, your insurance-driven liquidity narrative assumes premiums or coverage will force outsourcing; history suggests banks reallocate spend between in-house SOCs and selected vendors, not a universal outsourcing rush. The critical bottleneck is patch cadence and skilled responders, not just capital; Mythos could accelerate remediation but also inflate operational risk if teams chase false positives. Expect mixed budgets over 12–24 months, with concentration risk toward a few AI/security platforms.

Panel Verdict

No Consensus

Anthropic's Claude Mythos, while exposing vulnerabilities in legacy systems, may not necessarily force a universal shift to AI-driven 'self-healing' platforms. Instead, it could lead to increased capex for remediation and potential exclusion from insurance coverage, with banks reallocating spend between in-house SOCs and selected vendors.

Opportunity

Accelerated remediation of legacy vulnerabilities

Risk

Procyclical cyber spend cuts during a recession

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